context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
tool use — A model's ability to call external functions — run code, search the web, edit files — instead of only generating text.
grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.
system prompt — The standing instructions a model receives before any user input — defining its role, rules, tools, and tone for the whole conversation.
Why it matters
Trajectory-level judges plus DSPy turn agent evals from a scoreboard into an optimizer: calibrate the judges on human labels first, then let them tune the agent's system promptThe standing instructions a model receives before any user input — defining its role, rules, tools, and tone for the whole conversation.Full definition →.
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videoHow Evals and Prompts Shape Agent Behavior — Preetika Bhateja & Daniel Bump, YouTube AdsAI Engineer